Multimodal Sleep Stage Detection On Sleep Edf 1
Métriques
Macro-F1
Accuracy
Cohen's kappa
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Macro-F1 | Accuracy | Cohen's kappa | Paper Title | Repository |
|---|---|---|---|---|---|
| CatBoost | 0.795 | 83.6% | 0.765 | Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring | - |
| Linear model | 0.792 | 82.9% | 0.759 | Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring | - |
| Scratch SeqSleepNet+ (EEG+EOG) | - | 79.6% | - | Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning | - |
0 of 3 row(s) selected.